1. Field
The present work relates generally to communications and, more particularly, to estimating the channel impulse response (CIR) of a communication channel, for use as a demodulation reference.
2. Background
A typical problem in a communications system (whether wireless or wired) is estimating the impulse response of the communication channel linking the transmitting device to the receiving device. This channel may include radio frequency filters and distortion sources in the transmitter and receiver, as well as the actual propagation medium (whether wireless or wired) over which the communication signal travels. As is well-known in the art, when estimated in the discrete time domain, the CIR estimate may be denoted byĥ(n;m)=h(n;m)+u(n;m)   (1)where h(n;m) is the true (complex valued) CIR at lag n and update time m, with power σh2(n), and where u(n;m) is additive noise with power σu2(n).
When the resulting estimated CIR is used as a reference for demodulating data in the receiver, the additive noise u(n; m) adversely affects the receiver performance and hence limits the data transmission reliability and throughput. To mitigate this noise, conventional systems commonly filter the CIR estimates across updates of the sample (i.e. time) domain estimator to form a low pass filtered CIR estimate ĥƒ(n;m), and then apply a threshold to each tap of that filtered CIR estimate (based on the tap magnitude or squared magnitude), in order to force “weak” taps to zero.
The thresholding ensures that taps that have very little signal component (and are hence essentially pure noise) have minimum affect on the final performance. One complication with this approach is choosing the threshold value. In particular, at low carrier-to-interference-plus-noise ratios (CINRs), it is beneficial to zero out the majority of the taps (i.e., choose a low threshold) since the noise is the chief contributor to the overall performance. On the other hand, as the noise level drops, the information in the “weak” CIR taps becomes more important for operation at high spectral efficiencies. The problem is to process the raw estimates correctly under all operating conditions to efficiently extract the maximum information for use in data demodulation. In general, the choice of the threshold value should preferably be matched to the operating environment.
The thresholding approach requires considerable oversight in order to handle/manage different extreme (and time-varying) channel conditions. A further complication arises because the thresholding approach can result in spectral re-growth in the frequency domain channel response, which can be detrimental.
It is therefore desirable in view of the foregoing to provide for time domain CIR estimation that mitigates the effects of additive noise on receiver performance and while avoiding the aforementioned difficulties associated with conventional filtering/thresholding approaches.